Critic-over-Actor-Critic Modeling: Finding Optimal Strategy in ICU ...
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In this paper, we present a study of a multi-agent RL framework which involves a Critic in semi-offline mode criticizing over an online Actor-Critic network.
It solves the problem in sequential decisions by optimizing reward-punishment through experimentation of the distinct actions in an environment. Unlike ...
In this paper, we present a study of a multi-agent RL framework which involves a Critic in semi-offline mode criticizing over an online Actor-Critic network.
Sep 28, 2024 · An optimal parameter finding algorithm based on SAC(Soft-Actor-Critic) is proposed to solve the problem that the compensation term parameters ...
Dec 17, 2022 · In this study, we develop a new deconfounding actor-critic network (DAC) to learn optimal DTR policies for patients. To alleviate confounding ...
In this paper, we present a study of a multi-agent RL framework which involves a Critic in semi-offline mode criticizing over an online Actor-Critic network, ...
Critic-over-Actor-Critic Modeling: Finding Optimal Strategy in ICU Environments ... Lovatto, Decision-aware model learning for actor-critic methods: when theory ...
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Apr 25, 2024 · Riazat Ryan, Ming Shao : Critic-over-Actor-Critic Modeling: Finding Optimal Strategy in ICU Environments. IEEE Big Data 2022: 1356-1361 ...
Critic-over-Actor-Critic Modeling: Finding Optimal Strategy in ICU Environments. (2022). Not Available. Content Type: proceedings-article. Conference: 2022 IEEE ...
This study proposes an actor-critic reinforcement learning optimization strategy using a DNN surrogate model, which was developed from a validated mathematical ...
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